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View Code? Open in Web Editor NEWA full-fledged yet minimalistic CUDA-based convolutional neural network library from scratch in C++
License: MIT License
A full-fledged yet minimalistic CUDA-based convolutional neural network library from scratch in C++
License: MIT License
Two things to do:
When and how to allocate GPU/CPU memory?
Setup project directory structure
Build Scripts: CMakelists
Discuss, design and implement basic data structures:
Tensor
Packet
Nodes(?)
To implement a shared data holder for gradients of activations for efficient GPU memory usage.
put a reference of Tensors into a list in the global session whenever Tensor::CreateTensorCPU/GPU are called.
call session->free_tensors() to free all the memory allocated to the Tensors and set references to NULLs.
Discuss and select a unit test framework
Discuss and decide if to implement sessions and graphs
Current implementation seems buggy. Should look into it.
CMakelists
Working Conv2D Layer (Gaussian blur demo)
Discuss and finalize the parameter initialization design: When and how to initialize the model parameters?
Discuss and select a Unit Test Framework
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